A Collaborative Access Control Model for Shared Items in Online Social Networks

The recent emergence of online social networks (OSNs) has changed the communication behaviors of thousand of millions of users. OSNs have become significant platforms for connecting users, sharing information, and a valuable source of private and sensitive data about individuals. While OSNs insert constantly new social features to increase the interaction between users, they, unfortunately, offer primitive access control mechanisms that place the burden of privacy policy configuration solely on the holder who has shared data in her/his profile regardless of other associated users, who may have different privacy preferences. Therefore, current OSN privacy mechanisms violate the privacy of all stakeholders by giving one user full authority over another’s privacy settings, which is extremely ineffective. Based on such considerations, it is essential to develop an effective and flexible access control model for OSNs, accommodating the special administration requirements coming from multiple users having a variety of privacy policies over shared items. In order to solve the identified problems, we begin by analyzing OSN scenarios where at least two users should be involved in the access control process. Afterward, we propose collaborative access control framework that enables multiple controllers of the shared item to collaboratively specify their privacy settings and to resolve the conflicts among co-controllers with different requirements and desires. We establish our conflict resolution strategy’s rules to achieve the desired equilibrium between the privacy of online users and the utility of sharing data in OSNs. We present a policy specification scheme for collaborative access control and authorization administration. Based on these considerations, we devise algorithms to achieve a collaborative access control policy over who can access or disseminate the shared item and who cannot. In our dissertation, we also present the implementation details of a proof-of-concept prototype of our approach to demonstrate the effectiveness of such an approach. With our approach, sharing and interconnection among users in OSNs will be promoted in a more trustworthy environment

Designing Secure Access Control Model in Cyber Social Networks

Nowadays, information security in online communication has become an indisputable topic. People prefer pursuing their connection and public relations due to the greater flexibility and affordability of online communication. Recently, organizations have established online networking sites concerned with sharing assets among their employees. As more people engage in social network, requirements for protecting information and resources becomes vital. Over the years, many access control methods have been proposed. Although these methods cover various information security aspects, they have not provided an appropriate approach for securing information within distributed online networking sites. Moreover, none of the previous research provides an access control method in case an existing resource encompassing various parts and each part has its own accessing control policy. In this research, we investigate the access control requirements in order to conserve data and encompassed resources, which are shared in the social network, from users with unapproved access. Under the proposed method, users are able to define policies easily to protect their individual information and resources from unauthorized users. In addition, requestors are able to generate inquiries in easy and efficient way. We define an appropriate format to present rules and queries, which are converted from policies and inquiries respectively. The proposed approach defines a method in case a user would like to access a resource belonging to another user where both users are members of different online networking sites. In order to add more flexibility, this method controls access to data and resources by evaluating requestor’s attributes, object’s attributes, action or operation taken by requestor, environmental condition, and policies which are created by users or a super user of social network to protect the users’ resources. This approach is called Policy-Based Attribute Access Control (PBAAC). The policies defined to secure a resource may conflict with other policies. The proposed method offers an appropriate solution to resolve this issue. Due to achievement of better performance with regards to efficiency, this research analyzes the method to compromise simple rules, complex rules, or rules including several attributes. The results prove that simple rules provide better performance

A survey of statistical network models

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.Comment: 96 pages, 14 figures, 333 reference

Teak: A Novel Computational And Gui Software Pipeline For Reconstructing Biological Networks, Detecting Activated Biological Subnetworks, And Querying Biological Networks.

As high-throughput gene expression data becomes cheaper and cheaper, researchers are faced with a deluge of data from which biological insights need to be extracted and mined since the rate of data accumulation far exceeds the rate of data analysis. There is a need for computational frameworks to bridge the gap and assist researchers in their tasks. The Topology Enrichment Analysis frameworK (TEAK) is an open source GUI and software pipeline that seeks to be one of many tools that fills in this gap and consists of three major modules. The first module, the Gene Set Cultural Algorithm, de novo infers biological networks from gene sets using the KEGG pathways as prior knowledge. The second and third modules query against the KEGG pathways using molecular profiling data and query graphs, respectively. In particular, the second module, also called TEAK, is a network partitioning module that partitions the KEGG pathways into both linear and nonlinear subpathways. In conjunction with molecular profiling data, the subpathways are ranked and displayed to the user within the TEAK GUI. Using a public microarray yeast data set, previously unreported fitness defects for dpl1 delta and lag1 delta mutants under conditions of nitrogen limitation were found using TEAK. Finally, the third module, the Query Structure Enrichment Analysis framework, is a network query module that allows researchers to query their biological hypotheses in the form of Directed Acyclic Graphs against the KEGG pathways